code: def test_arbitrary_encoding_automatically_find_variables_ignore_format(
      df_enc_numeric,
  ):
      encoder = OrdinalEncoder(
          encoding_method="arbitrary",
          variables=None,
          ignore_format=True,
      )
      X = encoder.fit_transform(df_enc_numeric[["var_A", "var_B"]])
  
      # expected output
      transf_df = df_enc_numeric[["var_A", "var_B"]].copy()
      transf_df["var_A"] = [
          0,
          0,
          0,
          0,
          0,
          0,
          1,
          1,
          1,
          1,
          1,
          1,
          1,
          1,
          1,
          1,
          2,
          2,
          2,
          2,
      ]
      transf_df["var_B"] = [
          0,
          0,
          0,
          0,
          0,
          0,
          0,
          0,
          0,
          0,
          1,
          1,
          1,
          1,
          1,
          1,
          2,
          2,
          2,
          2,
      ]
  
      # test init params
      assert encoder.encoding_method == "arbitrary"
      assert encoder.variables is None
      # test fit attr
      assert encoder.variables_ == ["var_A", "var_B"]
      assert encoder.encoder_dict_ == {
          "var_A": {1: 0, 2: 1, 3: 2},
          "var_B": {1: 0, 2: 1, 3: 2},
      }
      assert encoder.n_features_in_ == 2
      # test transform output
      pd.testing.assert_frame_equal(X, transf_df)
  
file_path: feature_engine/tests/test_encoding/test_ordinal_encoder.py
imports: import numpy
  import pandas
  import pytest
  from feature_engine.encoding import OrdinalEncoder
label_desc: Use image node_id 9 for calling a global function with example usage: test_arbitrary_encoding_automatically_find_variables_ignore_format(df_enc_numeric) without return types